Intensity-Based Registration for Lung Motion Estimation
Kunlin Cao, Kai Ding, Ryan E. Amelon, Kaifang Du, Joseph M. Reinhardt, Madhavan Lakshmi Raghavan, Gary E. Christensen · Biological and medical physics series · 2013
Image registration plays an important role within pulmonary image analysis. The task of registration is to find the spatial mapping that brings two images into alignment. Registration algorithms designed for matching 4D lung scans or two 3D scans acquired at different inflation levels can catch the temporal changes in position and shape of the region of interest. Accurate registration is critical to post-analysis of lung mechanics and motion estimation. In this chapter, we discuss lung-specific adaptations of intensity-based registration methods for 3D/4D lung images and review approaches for assessing registration accuracy. Then we introduce methods for estimating tissue motion and studying lung mechanics. Finally, we discuss methods for assessing and quantifying specific volume change, specific ventilation, strain/ stretch information and lobar sliding. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.